Pain accounts for 20-40% of primary care appointments during childhood and adolescence with musculoskeletal pain as a principal pain complaint. Pain in childhood is significant because it increases risk for pain, disability, and psychiatric disorders in adulthood. However, the mechanisms underlying the transition from acute to chronic pain in children are not known. Using a combination of psychophysical and psychological assessment, the central aim of this proposal is to understand the mechanisms that contribute to the transition from acute to chronic musculoskeletal pain in children and adolescents. The long-term goal of this K23 award is for the candidate to establish a programmatic line of patient-oriented research focused on identification of at- risk youth and prevention of chronic pain. The K23 candidate is an acting assistant professor in the Department of Anesthesiology and Pain Medicine at the University of Washington. The candidate proposes a five-year training plan with the support of faculty mentors who have expertise in pediatric pain, laboratory pain assessment, and prevention research to obtain instruction in state-of-the-art conditioned pain modulation assessment, prevention research, and training in pain assessment, diagnosis, and treatment in primary care. The University of Washington and Seattle Children's Research Institute provide excellent institutional support and resources for this award. The research plan involves three studies. Study 1 will compare clinical phenotypes of youth with acute musculoskeletal pain, chronic musculoskeletal pain, and healthy pain-free youth. Study 2 will prospectively follow a sample of youth with acute musculoskeletal pain in primary care to identify predictors of chronic pain development. Study 3 will pilot a web-based behavioral intervention for early treatment of chronic pain in primary care. These studies will lay the groundwork for future investigations examining profiles or clinical phenotypes of children in primary care who are at-risk for chronic pain; data that can inform a predictive model of chronic pain development.